In March, artificial intelligence flagged something resembling smoke on a camera feed from Arizona’s Coconino National Forest. Human reviewers determined it was not cloud or dust, then notified the Arizona forest service and Arizona’s largest electric utility, Arizona Public Service (APS). The alert corresponded to the early stages of the Diamond Fire, which firefighters contained before it grew beyond about 7 acres (2.8 hectares).

The incident reflects a broader push across wildfire-prone parts of the Western United States, where record heat and low snowpack increase wildfire risk. APS has nearly 40 active AI smoke-detection cameras and plans to expand to 71 by summer’s end; Arizona’s fire agency has deployed seven cameras. In Colorado, Xcel Energy has installed 126 cameras and aims to cover seven of the eight states it serves by year’s end. California is described as having a network of about 1,240 AI-enabled cameras.

Officials and experts say the systems aim to shorten response times, with one APS meteorologist citing an average notification about 45 minutes faster than the first 911 call. The reports also note limitations, including false alarms and that detection does not determine firefighting actions, which still require human decision-making.